FPGA-based Volleyball Player Tracker

摘要

The significant challenge facing sport science is how to grasp the flow of the game and analyze the situation of a match. The use of information technology will facilitate to achieve the goal. The technical issues from the practical application perspective can be classified into three main points: computation speed, system size and complex data analysis considering the accuracy. In this paper, for accelerating image recognition and object tracking, we propose a one-dimensional data pipeline architecture on a field-programmable gate array (FPGA). It satisfies both of high-speed streaming computation and small-sized circuits by considering spatiotemporal data dependence. Volleyball games have been chosen as a target application. The proposed system will identify the position of six volleyball players within real time. The design on an FPGA includes pre-processing, color filtering, digitalization, noise reduction, template matching, and so on. The design was implemented and evaluated on Atlys Spartan-6 FPGA Trainer Board with one XILINX Spartan-6 LX45 FPGA. The computational performance achieves 100 frames per second at SVGA 800 by 600 pixel resolution. And our design has good scalability; the performance can easily be enhanced when the larger FPGA is used. The proposed system is also compact, which is composed of one Atlys board and one Atlys VmodCAM stereo-camera board. The average-accuracy rates of pregame situation and during a match are 87.1% and 65.7%, respectively. Since the input is streaming data, we can improve the accuracy by considering the previous and the next frames. They could be improved to 90.4% and 72.2%, respectively, when we adopt template matching with a moving average filter.